Aura-2 is a context-aware text-to-speech (TTS) model that applies natural pacing, expressiveness, and fillers based on the context of the provided text. The quality of your text input directly impacts the naturalness of the audio output.
Provider: All Deepgram models | Cloudflare Workers AI
https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1/chat/completionsInstall: pip install openai
import os
from openai import OpenAI
account_id = os.environ["CLOUDFLARE_ACCOUNT_ID"]
client = OpenAI(
api_key=os.environ["CLOUDFLARE_API_TOKEN"],
base_url=f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1",
)
response = client.chat.completions.create(
model="@cf/deepgram/aura-2-es",
messages=[
{"role": "user", "content": "Hello, how are you?"},
],
max_tokens=1024,
)
print(response.choices[0].message.content)Additional examples: Basic invoke, REST API (any task)
| Parameter | Type | Description |
|---|---|---|
| max_tokens | integer | Maximum tokens to generate. (≥1) |
| temperature | float | Controls randomness. Supported range varies by model. (≥0) |
| stream | boolean | Stream response chunks as they are generated. Default: false. |
Call text generation and embedding models with OpenAI-compatible client libraries using the account-scoped Workers AI base URL.
Run any Workers AI model, including image, speech, and embedding models, through the account-scoped /ai/run endpoint.
List available models, tasks, and per-model properties with the Workers AI models search API.